Though Stevie Nicks didn’t sing about them, firms are getting older too. The age of companies is rising in the United States, just as the rate at which Americans are starting firms is declining. Fewer startups and older firms—a trend that began in 1980—could have a number of negative consequences, an important one being slower productivity growth. But how much is the aging of companies actually affecting productivity? A new paper released this week by the National Bureau of Economic Research takes a look.

The paper—by economists Titan Alon and David Berger of Northwestern University, Robert Dent of Nomura Securities, and Benjamin Pugsley of the University of Notre Dame—takes two approaches to figuring out how much the increasing age of firms may be affecting the pace of productivity growth. The first is to use data from the U.S. Census Bureau to create data on labor productivity of firms over their lifecycles. These data on the lifecycles tell us how much productivity growth differs for firms across the age spectrum. The profiles show that young firms have significantly higher productivity growth and that this growth falls off very quickly. During the first year of business, brand new firms’ productivity grows by 15 percent on average. But that growth falls very quickly over the next few years and by the fifth year, the average productivity growth is essentially zero.

What accounts for this downward trend in productivity growth? The authors decompose the lifecycle profile, attributing different portions of the trends to specific factors. The largest factor behind the large productivity growth of young firms is reallocation of resources toward more productive firms, accounting for about two-thirds of productivity growth. The other one-third is due to selection, or the fact that less-productive companies are failing more than the more productive companies.

The economists then calculate the level of productivity growth we might have seen in 2014 if the startup rate had stayed at its 1980 level and if the distribution of companies hadn’t aged over the next 34 years. According to this exercise, labor productivity would have been 3.1 percent higher in 2014 or, put differently, labor productivity would have been 0.1 percent higher each year over that period. Assuming that labor productivity increases are fully passed through to household income, median household income would have been about $1,600 higher under this situation.

The four economists also run several regression analyses on the relationship between increased startups and productivity growth across states and metropolitan statistical areas. While they want to understand how startup rates affect productivity, productivity likely has an impact on startup rates as well. People will probably start more businesses if an area has strong and growing productivity. To get around this potential problem, the authors “instrument” for new business creation by using demographic changes in the state or metropolitan statistical areas and—in the second analysis—the amount of house-price increases during the 2002–2006 bubble that were due to speculation. The logic is that areas with more population growth will see more people start businesses due to increased demand, and places that saw increased access to collateral for loans from house-price increases also will have more startups—neither factor is likely to be influenced by productivity growth. The results here are broadly consistent with the earlier findings: Fewer startups and older firms lead to slower productivity growth.

The authors don’t look at the reasons why there is less startup activity now, but increasingly researchers are looking at the role of increased market power. Productivity growth by itself won’t lead to strong increases in living standards, but living standards are unlikely to rise without it. Understanding what’s led to fewer new firms in the U.S. economy—whether it be corporate consolidation or other factors—may be more important than many economists and economic policymakers currently realize.